Introduction

Content

  • Marginalization and conditioning
  • Bayes’ theorem
  • Review of probability distributions
  • Likelihood
  • Monte Carlo integration

Readings

Warning

These readings should be completed before class, to ensure timely understanding and let us discuss the concepts together through various examples and case studies — the strict minimum being the course notes.

Complementary readings

Warning

Complementary readings are additional sources of information that are not required readings, but may be useful substitutes. Sometimes, they go beyond the scope of what we cover and provide more details.

  • Chapter 1 of Wood (2015)
  • Chapter 4 and 6.1 of Davison (2003)
  • Chapters 2 and 3 of Robert & Casella (2004)
  • Chapters 1–6 of Casella & Berger (2002)

Slides

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References

Casella, G., & Berger, R. L. (2002). Statistical inference (2nd ed.). Duxbury.
Davison, A. C. (2003). Statistical models. Cambridge University Press.
Robert, C. P., & Casella, G. (2004). Monte Carlo statistical methods (2nd ed.). Springer. https://doi.org/10.1007/978-1-4757-4145-2
Wood, S. N. (2015). Core statistics. Cambridge University Press. https://doi.org/10.1017/cbo9781107741973